Deloitte Survey: What Are The 7 Capabilities Central To AI And Digital Transformation
By: Bernard Marr | Forbes
heavily in digital transformation has almost doubled in the past year.
The accounting and services giant questioned 1,200 executives at organizations of at least 500 people with above $250 million in revenue, finding that 19% planned to invest $20 million or more during 2019. When asked the same question at the start of 2018, 10% gave that answer.
The term “digital transformation” has come to mean steps that move an organization towards adopting data-driven business models, typically involving artificial intelligence (AI), big data and predictive analytics technology.
The survey also found that budgets dedicated to this transformation at medium to large-sized companies increased from an average of $11 million to $13.5 million this year.
However, it also highlighted the finding that most organizations still report a gap between their investment in this technology and the impact it is having on key performance indicators such as profits, revenues and customer satisfaction.
In an effort to understand this, it identifies 7 “pivots” - capabilities that, when developed, contribute towards a business successfully bringing about positive growth through a technology initiative.
It found that "higher maturity" organizations – those who had progressed their digital transformation to the point where they are driving positive growth - deploy an average of 40 initiatives targeting these pivots capabilities, suggesting they are indeed a contributing factor.
Deloitte’s chief digital officer and head of innovation, Ragu Gurumurthy, explained to me that three of these pivots stood out as "foundational," and solving challenges around them often opens the pathways to digital transformation at medium and large-sized organizations.
He told me “The first things companies should do is focus on data mastery and infrastructure, as well as their talent.
In terms of infrastructure, companies need to create flexible and secure systems that are able to balance security and privacy with the need to flex capacity as business demand changes.
Data mastery is about aggregating, activating and monetizing data that is still often siloed and underutilized in order to generate better products, services and business operations that will drive business success.
“Those are the enabling pivots that allow us to begin thinking about transformation.”
Data mastery involves generating value from data to increase the efficiency and effectiveness of business processes.
“People say that data is the new oil in the digital economy, and yes, it is – but in the hydrocarbon era you didn’t need to own oil wells to become wealthy,” says Gurumurthy.
“You don’t need to own all of the data – you just need to know what to do with the data you do own.”
What he means by this is while companies like Google and Facebook may have become giants of the digital age by monetizing the “data crumbs” left by users as they use their platforms and services, not all businesses will need to take this route.
“I would say that 90% of the corporate world is not going to capture value through naked monetization of their data assets the way Google or Amazon does. For the most part, they will capture data to increase the efficiency and effectiveness of their company.”
That could mean finding better ways of targeting customers and understanding their behavior and optimizing marketing and retail channels based on the data they collect. In other words, the majority of companies approaching levels of digital maturity where their data becomes a valuable asset is doing so by creating growth for existing, core products and services, rather than creating new ones from their "data exhaust."
“It’s about creating a secure environment, where you can launch applications fast and remove the friction in your operations, and think about how you interact with your customers – this is made possible by investing in and understanding your data infrastructure.”
The next key pivot – talent – revolves around the way data is used to understand and nurture a business’s most vital asset – it’s employees.
“This is actually the hardest thing to do,” explains Gurumurthy. “One can figure out cloud migration strategies, one can figure out how to collect and store data, and how to run analytics on it, but its harder to manage change around talent.
“If you ask people what their biggest challenges are in digital transformation they will say it is the talent deficit – there's often resistance to cultural change and a deficiency in the kind of talent that's needed.”
This is challenging because of the different mindset which becomes necessary when transitioning to data-driven business models, particularly when human staff are being asked to put their faith in technology like artificial intelligence and advanced analytics which may result in insights and observations which seem counter-intuitive to many of us.
"It's often about retraining the talent – another phrase we use is the ‘digital mindset,'" explains Gurumurthy.
"It's about speed of reaction and action, which needs to be faster than ever before. How do people develop products? How do people react to customer needs and run their operations? In every aspect of business people need to be doing things faster – think about agile – it's not just agile software development any more, we now have agile strategy and agile planning.
"It comes down to the speed with which one can leverage data to make decisions and then iterate them – creating a self-learning loop – that's the heart of the ‘digital mindset.' And creating that in the talent is a hard challenge."
Once the foundations of a digital transformative strategy have been built around data master and infrastructure, and talent, then work can begin on the other pivots identified as key to moving towards a “mature” digital transformation.
Ecosystem engagement – partnering with external businesses such as tech incubators, R&R companies, and start-ups to access their resources and talent.
Intelligent workflows – continuously rethinking processes to maximize the capabilities of both, people and technology, and create environments where they complement each other perfectly to deliver maximum business outcomes.
Unified customer experience – delivering seamless and efficient, as well as enjoyable and immersive customer experiences based on a 360-degree understanding of customers that is shared companywide.
Business model adaptability – continuously re-evaluating and adjusting the business models and revenue streams used by the business.
All of these are explored in depth in the full report.
So, what is holding businesses back from unlocking the full potential of digital transformation? Well, aside from the talent deficiency already mentioned (cited by 36% as a barrier), challenges posed by existing, legacy operating models, and a lack of a strategy for clearly prioritizing adoption of transformative technology were cited by 49% and 45% of respondents, respectively.
And while organizations in the technology, media, and telecommunications sectors were the most likely to have reached the level of maturity that brings bottom-line growth, one surprise was that, once they have made the grade, benefits across all sectors are broadly similar.
Commenting on this, Gurumurthy said “What we found from the results of the survey is that once you’re digitally mature, the bump you’re getting in terms of valuation and profit margins is actually looking similar across all sectors – this was surprising to me as I was expecting tech-centric companies to see a higher kicker, but that was not the case.”
This makes it clear that whatever industry you’re in, the rewards of driving growth through digital transformation are there for the taking.